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Such structured sequences can represent\nseries of frames in videos, spatio-temporal measurements on a network of\nsensors, or random walks on a vocabulary graph for natural language modeling.\nThe proposed model combines convolutional neural networks (CNN) on graphs to\nidentify spatial structures and RNN to find dynamic patterns. We study two\npossible architectures of GCRN, and apply the models to two practical problems:\npredicting moving MNIST data, and modeling natural language with the Penn\nTreebank dataset. Experiments show that exploiting simultaneously graph spatial\nand dynamic information about data can improve both precision and learning\nspeed.","url_abs":"http://arxiv.org/abs/1612.07659v1","url_pdf":"http://arxiv.org/pdf/1612.07659v1.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"structured-sequence-modeling-with-graph","repo_url":"https://github.com/youngjoo-epfl/gconvRNN","is_official":1,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"tf","reach":null},{"paper_slug":"structured-sequence-modeling-with-graph","repo_url":"https://github.com/andymogul/gcrnn_revised","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"tf","reach":{"status":"ok","spdx":"MIT"}},{"paper_slug":"structured-sequence-modeling-with-graph","repo_url":"https://github.com/benedekrozemberczki/pytorch_geometric_temporal","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"pytorch","reach":null},{"paper_slug":"structured-sequence-modeling-with-graph","repo_url":"https://github.com/dariush-salami/gcn-gesture-recognition","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"pytorch","reach":{"status":"ok","spdx":"MIT"}},{"paper_slug":"structured-sequence-modeling-with-graph","repo_url":"https://github.com/mdeff/paper-cnn-graph-recurrent-iclr2017","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"none","reach":{"status":"ok","spdx":"CC-BY-4.0"}}],"tasks":[{"task_slug":"language-modeling","task_name":"Language Modeling"},{"task_slug":"language-modelling","task_name":"Language Modelling"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":"https://app.syntology.ai/?focus=1612.07659","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"1612.07659"}},"developers":"https://syntology.ai/developers","read_at":"2026-09-24T18:15:14+00:00","read_at_is":"when the build read Syntology's graph, not when any sample ran","claim":"Per-sample execution status on synthesized fixtures; not a correctness claim about the paper. 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